SOTAVerified

3D Object Detection

3D Object Detection is a task in computer vision where the goal is to identify and locate objects in a 3D environment based on their shape, location, and orientation. It involves detecting the presence of objects and determining their location in the 3D space in real-time. This task is crucial for applications such as autonomous vehicles, robotics, and augmented reality.

( Image credit: AVOD )

Papers

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Showing 1526–1550 of 1576 papers

TitleStatusHype
SECOND: Sparsely Embedded Convolutional DetectionCode2
Focal Loss in 3D Object DetectionCode0
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery—0
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic ImageryCode0
Holistic 3D Scene Parsing and Reconstruction from a Single RGB ImageCode0
PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point CloudCode0
Leveraging Pre-Trained 3D Object Detection Models For Fast Ground Truth Generation—0
Symmetry Aware Evaluation of 3D Object Detection and Pose Estimation in Scenes of Many Parts in Bulk—0
Multi-Level Fusion Based 3D Object Detection From Monocular Images—0
3D Object Detection With Latent Support Surfaces—0
CubeSLAM: Monocular 3D Object SLAMCode1
Scene Understanding Networks for Autonomous Driving based on Around View Monitoring System—0
BirdNet: a 3D Object Detection Framework from LiDAR informationCode1
Falling Things: A Synthetic Dataset for 3D Object Detection and Pose Estimation—0
Complex-YOLO: Real-time 3D Object Detection on Point CloudsCode2
A General Pipeline for 3D Detection of Vehicles—0
SBNet: Sparse Blocks Network for Fast InferenceCode0
Joint 3D Proposal Generation and Object Detection from View AggregationCode0
PointFusion: Deep Sensor Fusion for 3D Bounding Box EstimationCode0
SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance SegmentationCode0
Frustum PointNets for 3D Object Detection from RGB-D DataCode1
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object DetectionCode1
Fusing Bird View LIDAR Point Cloud and Front View Camera Image for Deep Object Detection—0
3D-SSD: Learning Hierarchical Features from RGB-D Images for Amodal 3D Object Detection—0
2D-Driven 3D Object Detection in RGB-D Images—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78—Unverified
2MMFusion-eNDS0.77—Unverified
3MegFusionNDS0.77—Unverified
4RacoonPowerNDS0.76—Unverified
5BEVFusion-eNDS0.76—Unverified
6DeepInteraction-largeNDS0.76—Unverified
7DeepInteraction-eNDS0.76—Unverified
8DAANDS0.75—Unverified
9FusionVPENDS0.75—Unverified
10CenterPoint-FusionNDS0.75—Unverified